File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Evaluation metric for multiple-bug localization with simple and complex predicates

TitleEvaluation metric for multiple-bug localization with simple and complex predicates
Authors
KeywordsStatistical debugging
Debuggers
Evaluation metrics
Program bugs
Program execution
Issue Date2012
PublisherIEEE.
Citation
The 19th Asia-Pacific Software Engineering Conference (APSEC 2012), Hong Kong, 4-7 December 2012. In Asia Pacific Software Engineering Conference Proceedings, 2012, v. 1, p. 288-293 How to Cite?
AbstractStatistical debugging is a technique that mines data obtained from software executions in order to identify the program statements that are relevant to program bugs. Specifically' program predicates are injected into the program during compilation and statistics about those predicates are collected during the program execution. When bugs are found but the developers have no clue where the bugs are' they may call such a statistical debugger for help. The debugger ranks the injected predicates according to their statistical relevancy to bugs and presents the suspicious ones to the developers. When a bug is found and fixed' but the updated program still contains (some other) bugs' the preceding procedure is iterated until all bugs are fixed. There are two types of predicate-based statistical debugger: one type returns only simple predicates' another type returns only complex predicates. We envision that the next wave of statistic debuggers should be able to return both' depending on the kinds of bugs manifested in the software. In this paper' we take the first step and study the metrics for evaluating the effectiveness of statistical debuggers that can return both types of predicate predictors (simple or complex). © 2012 IEEE.
DescriptionSession 3C: Software Project Management and Applications
Persistent Identifierhttp://hdl.handle.net/10722/164928
ISBN
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Yen_US
dc.contributor.authorLo, Een_US
dc.contributor.authorKao, CMen_US
dc.date.accessioned2012-09-20T08:12:27Z-
dc.date.available2012-09-20T08:12:27Z-
dc.date.issued2012en_US
dc.identifier.citationThe 19th Asia-Pacific Software Engineering Conference (APSEC 2012), Hong Kong, 4-7 December 2012. In Asia Pacific Software Engineering Conference Proceedings, 2012, v. 1, p. 288-293en_US
dc.identifier.isbn9780769549224-
dc.identifier.issn1530-1362-
dc.identifier.urihttp://hdl.handle.net/10722/164928-
dc.descriptionSession 3C: Software Project Management and Applications-
dc.description.abstractStatistical debugging is a technique that mines data obtained from software executions in order to identify the program statements that are relevant to program bugs. Specifically' program predicates are injected into the program during compilation and statistics about those predicates are collected during the program execution. When bugs are found but the developers have no clue where the bugs are' they may call such a statistical debugger for help. The debugger ranks the injected predicates according to their statistical relevancy to bugs and presents the suspicious ones to the developers. When a bug is found and fixed' but the updated program still contains (some other) bugs' the preceding procedure is iterated until all bugs are fixed. There are two types of predicate-based statistical debugger: one type returns only simple predicates' another type returns only complex predicates. We envision that the next wave of statistic debuggers should be able to return both' depending on the kinds of bugs manifested in the software. In this paper' we take the first step and study the metrics for evaluating the effectiveness of statistical debuggers that can return both types of predicate predictors (simple or complex). © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE.-
dc.relation.ispartofAsia Pacific Software Engineering Conference Proceedingsen_US
dc.rightsAsia Pacific Software Engineering Conference Proceedings. Copyright © IEEE.-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectStatistical debugging-
dc.subjectDebuggers-
dc.subjectEvaluation metrics-
dc.subjectProgram bugs-
dc.subjectProgram execution-
dc.titleEvaluation metric for multiple-bug localization with simple and complex predicatesen_US
dc.typeConference_Paperen_US
dc.identifier.emailZhang, Y: yiweiz@microsoft.comen_US
dc.identifier.emailLo, E: ericlo@comp.polyu.edu.hk-
dc.identifier.emailKao, CM: kao@cs.hku.hk-
dc.identifier.authorityKao, CM=rp00123en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/APSEC.2012.37-
dc.identifier.scopuseid_2-s2.0-84874609196-
dc.identifier.hkuros209757en_US
dc.identifier.volume1-
dc.identifier.spage288-
dc.identifier.epage293-
dc.identifier.isiWOS:000332765100034-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 130509-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats